Many data manipulation scenarios involve converting a large quantity of input information from one format to another format. For example, assume that a user wishes to convert a collection of invoice records from an original format to a target format. For example, the user may wish to convert the invoice records into a native format that is used by his or her record-keeping software. If the collection of invoice records is small enough, the user may decide to perform this conversion in a manual manner. However, this task becomes increasingly impracticable as the size of the collection grows larger.
A user may alternatively address this task by writing a program which converts the records from an input format to a desired output format. For example, a user who is an expert in spreadsheet-related technology can write a macro program which performs this task. However, many users do not have the requisite skills and/or motivation to write such programs. Further, writing a satisfactory program can be a non-trivial and time-consuming task for even experienced users.
The above features and attendant potential shortcomings are presented by way of illustration. Existing data manipulation strategies may suffer from yet other shortcomings and challenges.